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Kvasir-VQA-x1-lora_260823-1829
me1adi/Kvasir-VQA-x1-lora_260823-1829
Kvasir-VQA-x1-lora_260823-1829 is a text generation model from me1adi. Use it when you need the model to write or continue text. It is set up for peft.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Generation
- Library
- peft
- Access
- Public
- Created
- Aug 23, 2026
- Updated
- Aug 23, 2026
- SHA
- a7235914
Try a prompt
Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
Kvasir-VQA-x1-lora_260823-1829
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4089
- Token Acc: 0.8573
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Use adamw_torch_fused with betas=(0.9,0.95) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 0.03
- num_epochs: 2.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Token Acc |
|---|---|---|---|---|
| 0.6074 | 0.1114 | 1000 | 0.6064 | 0.8035 |
| 0.5380 | 0.2228 | 2000 | 0.5472 | 0.8191 |
| 0.5199 | 0.3343 | 3000 | 0.5312 | 0.8215 |
| 0.5344 | 0.4457 | 4000 | 0.5069 | 0.8283 |
| 0.4680 | 0.5571 | 5000 | 0.4901 | 0.8312 |
| 0.4942 | 0.6685 | 6000 | 0.4727 | 0.8360 |
| 0.4518 | 0.7800 | 7000 | 0.4644 | 0.8396 |
| 0.4598 | 0.8914 | 8000 | 0.4593 | 0.8425 |
| 0.4164 | 1.0028 | 9000 | 0.4526 | 0.8438 |
| 0.4103 | 1.1142 | 10000 | 0.4401 | 0.8479 |
| 0.3861 | 1.2256 | 11000 | 0.4390 | 0.8485 |
| 0.3911 | 1.3371 | 12000 | 0.4342 | 0.8513 |
| 0.4091 | 1.4485 | 13000 | 0.4259 | 0.8492 |
| 0.3802 | 1.5599 | 14000 | 0.4209 | 0.8530 |
| 0.3847 | 1.6713 | 15000 | 0.4190 | 0.8545 |
| 0.3460 | 1.7828 | 16000 | 0.4133 | 0.8554 |
| 0.3598 | 1.8942 | 17000 | 0.4109 | 0.8563 |
| 0.3611 | 2.0 | 17950 | 0.4089 | 0.8573 |
Framework versions
- PEFT 0.19.1
- Transformers 5.15.1
- Pytorch 2.13.0+cu130
- Datasets 4.8.4
- Tokenizers 0.22.2
- Task
- Text Generation
- Library
- peft
- Created
- Aug 23, 2026
- Updated
- Aug 23, 2026